椭圆的分层抽样技术

Chung-Ming Wang, N. Hwang
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引用次数: 3

摘要

提出了一种有效的椭圆分层抽样技术。我们的技术为低失真磁盘采样提供了先前工作的扩展;它适用于正方形和椭圆之间的极地和同心圆地图。该映射保留了邻接性和分数面积,并且不需要任何数值计算。与之前的工作一样,同心映射显示出更好的性能。我们的技术在使用蒙特卡罗直接照明和蒙特卡罗路径跟踪的逼真图像合成中被证明是有用的。总之,所提出的技术是分层的,高效的,并且对于计算机图形学社区是可行的。源代码可在线获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Stratified Sampling Technique for an Ellipse
Abstract We present an efficient stratified sampling technique for an ellipse. Our technique provides extensions of pre vious work for sampling a disk with lowdistortion; it works for both polar and concentric maps between a square and an ellipse. The mapping preserves adjacency and fractional area, and does not require any numerical computation. As in the previous work, the concentric map demonstrates better performance. Our technique has proven useful in realistic image synthesis using Monte Carlo direct lighting and Monte Carlo path tracing. In conclusion, the proposed technique is stratified, efficient, and feasible for the computer graphics community. Source code is available online.
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